code: def test_user_defined_function_behavior(self):
      def count_above_mean(array):
          mean = np.mean(array)
          return np.where(array > mean)[0].size
  
      transformation = {
          "function": count_above_mean,
          "mode": "rolling",
          "window": 5,
      }
      transformed_ts = self.target.window_transform(
          transformation,
      )
      expected_transformed_series = TimeSeries.from_times_and_values(
          self.times,
          np.array([0, 1, 1, 2, 2, 2, 2, 2, 2, 2]),
          columns=["rolling_udf_5_0"],
      )
      assert transformed_ts == expected_transformed_series
  
      # test if a customized function name is provided
      transformation.update({"function_name": "count_above_mean"})
      transformed_ts = self.target.window_transform(
          transformation,
      )
      assert transformed_ts.components.to_list() == [
          f"{transformation['mode']}_{transformation['function_name']}_{str(transformation['window'])}_{comp}"
          for comp in self.target.components
      ]
  
file_path: darts/darts/tests/dataprocessing/transformers/test_window_transformations.py
imports: import itertools
  import numpy
  import pandas
  import pytest
  from darts import TimeSeries
  from darts.dataprocessing.pipeline import Pipeline
  from darts.dataprocessing.transformers import Mapper, WindowTransformer
label_desc: Use image node_id 3 for calling the TestTimeSeriesWindowTransform obj's underlying member method code with example usage: obj.test_user_defined_function_behavior() and returns: np